Mohamed–Chaker Larabi
- Computer Vision and Pattern Recognition top 2%
- Media Technology top 2%
- Cognitive Neuroscience
- Computer Graphics and Computer-Aided Design top 5%
- Signal Processing top 10%
- Co-authors
- Christine Fernández-MaloigneAldo MaaloufSid Ahmed FezzaMassimiliano CorsiniFaouzi Alaya CheikhLibor VášaKai WangGuillaume Lavoué
- Topics
- Image and Video Quality Assessment (37 papers)Visual Attention and Saliency Detection (24 papers)Advanced Vision and Imaging (19 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Graphics and Computer-Aided Design
- Journals
- IEEE AccessSensorsNeurocomputing
In The Last Decade
Mohamed–Chaker Larabi
74 papers receiving 481 citations
Peers
Comparison fields: 5 of 56
- Computer Vision and Pattern Recognition 420
- Media Technology 173
- Cognitive Neuroscience 88
- Computer Graphics and Computer-Aided Design 56
- Signal Processing 54
Countries citing papers authored by Mohamed–Chaker Larabi
This map shows the geographic impact of Mohamed–Chaker Larabi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mohamed–Chaker Larabi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed–Chaker Larabi more than expected).
Fields of papers citing papers by Mohamed–Chaker Larabi
This network shows the impact of papers produced by Mohamed–Chaker Larabi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mohamed–Chaker Larabi. The network helps show where Mohamed–Chaker Larabi may publish in the future.
Co-authorship network of co-authors of Mohamed–Chaker Larabi
This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed–Chaker Larabi. A scholar is included among the top collaborators of Mohamed–Chaker Larabi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mohamed–Chaker Larabi. Mohamed–Chaker Larabi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | On the improvement of 2D quality assessment metrics for omnidirectional images | 2 |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 4 | |
| 9 | A BLOCK LEVEL ADAPTIVE MV RESOLUTION FOR VIDEO CODING | 1 |
| 10 | 1 | |
| 11 | 21 | |
| 12 | 71 | |
| 13 | 3 | |
| 14 | 15 | |
| 15 | 4 | |
| 16 | Low-complexity enhanced lapped transform for image coding in JPEG XR / HD photo | 1 |
| 17 | 3 | |
| 18 | 1 | |
| 19 | 2 | |
| 20 | 0 |
About Mohamed–Chaker Larabi
Mohamed–Chaker Larabi is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 79 papers that have together received 490 indexed citations. Recurring topics across this work include Image and Video Quality Assessment (37 papers), Visual Attention and Saliency Detection (24 papers) and Advanced Vision and Imaging (19 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (420 citations), Media Technology (173 citations) and Computer Graphics and Computer-Aided Design (56 citations). Mohamed–Chaker Larabi has collaborated with scholars based in France, Norway and Algeria. Frequent co-authors include Christine Fernández-Maloigne, Aldo Maalouf, Sid Ahmed Fezza, Massimiliano Corsini, Faouzi Alaya Cheikh, Libor Váša, Kai Wang, Guillaume Lavoué, Kamel Mohamed Faraoun and Tania Pouli. Their work appears in journals such as IEEE Access, Sensors and Neurocomputing.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.